Curriculum vitae

I was born on November 29th, 1975 near Nancy. I received a B.Sc. in Biochemistry and a M.Sc. in Microbiology, Enzymology, and Nutrition from the Henri Poincaré University in Nancy. In the course of this training, I developed a strong interest for pluridisciplinarity and I decided to develop my research activites in the fields of molecular biology and bioinformatics.

In 1998, I started my PhD thesis in the Laboratory of RNA Maturation and Molecular Enzymology headed by Christiane Branlant (Centre National de la Recherche Scientifique - Université Nancy I), while collaborating with the MODBIO research group at Loria (Institut National de Recherche en Informatique et en Automatique, research unit INRIA Lorraine), headed at that time by Alexander Bockmayr. I studied, both by experiments and mathematical modeling, the splicing regulation of the human immunodeficiency virus RNA.

After having obtained my PhD in 2003, I joined the research unit INRIA Rhône-Alpes as a post-doctoral researcher in the HELIX research group, headed by Alain Viari. In 2006, I have been recruited as a research scientist (chargé de recherche) at INRIA. I continue working in the same research group on the mathematical modeling of regulatory networks in bacteria, in particular, the model bacterium Escherichia coli.

Current research

The adaptation of living organisms to their environment is controlled at the molecular level by large and complex networks of genes, mRNAs, proteins, metabolites, and their mutual interactions. Molecular biology has been quite successful in dissecting these networks down to the molecular details of the interactions. However, in order to understand the overall behavior of an organism, we must complement molecular biology with a more global view of cellular functioning, by means of mathematical and computational tools. The dynamic analysis of cellular interaction networks provides a means to tackle this question, by constructing mathematical models derived from experimental data on the network structure, and using simulation tools to predict the behavior of the system under a variety of conditions.

Following this methodology, I analyze the regulatory network controlling the adaptation and survival of the gut bacterium Escherichia coli to environmental stress conditions. Understanding environmental influences helps one to explain the distribution of microorganisms in nature and makes it possible to devise methods for controlling or enhancing microbial activities. Even though E. coli is one of the best studied organisms, it is currently little understood how stress signals are sensed and propagated throughout the network, so as to enable the bacterium to respond in an adequate way.

To address these questions, I develop kinetic models of the network, and study them by means of classical analysis and simulation tools. For large systems, this approach is difficult to apply, due to the lack of reliable values for the parameters and initial conditions. Moreover, the models consist of a large number of variables, are strongly nonlinear, and include different time scales. To deal with these problems, I use (quasi-steady-state and piecewise-linear) approximations that preserve the capacity of the models to account for essential dynamic properties of the system. This allows to analyze the [qualitative dynamics>art338] of the stress response network of E. coli and predict the response of the bacterium to nutritional stress.